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NAMEAlgorithm::Evolutionary::Op::Breeder - Even more customizable single generation for an evolutionary algorithm. SYNOPSISuse Algorithm::Evolutionary qw( Individual::BitString Op::Mutation Op::Crossover Op::RouletteWheel Op::Breeder); use Algorithm::Evolutionary::Utils qw(average); my @pop; my $number_of_bits = 20; my $population_size = 20; my $replacement_rate = 0.5; for ( 1..$population_size ) { my $indi = new Algorithm::Evolutionary::Individual::BitString $number_of_bits ; #Creates random individual $indi->evaluate( $onemax ); push( @pop, $indi ); } my $m = new Algorithm::Evolutionary::Op::Mutation 0.5; my $c = new Algorithm::Evolutionary::Op::Crossover; #Classical 2-point crossover my $selector = new Algorithm::Evolutionary::Op::RouletteWheel $population_size; #One of the possible selectors my $generation = new Algorithm::Evolutionary::Op::Breeder( $selector, [$m, $c] ); my @sortPop = sort { $b->Fitness() <=> $a->Fitness() } @pop; my $bestIndi = $sortPop[0]; my $previous_average = average( \@sortPop ); $generation->apply( \@sortPop ); Base ClassAlgorithm::Evolutionary::Op::Base DESCRIPTIONBreeder part of the evolutionary algorithm; takes a population and returns another created from the first METHODSnew( $ref_to_operator_array[, $selector = new Algorithm::Evolutionary::Op::Tournament_Selection 2 ] )Creates a breeder, with a selector and array of operators apply( $population[, $how_many || $population_size] )Applies the algorithm to the population, which should have been evaluated first; checks that it receives a ref-to-array as input, croaks if it does not. Returns a sorted, culled, evaluated population for next generation. SEE ALSOMore or less in the same ballpark, alternatives to this one
CopyrightThis file is released under the GPL. See the LICENSE file included in this distribution, or go to http://www.fsf.org/licenses/gpl.txt
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